SoroushVahidi/scidocs huggingface dataset:
FiDO: A Community-based Web Browsing Agent and CDN for Challenged Network Environments
(2017)

Homes located on tribal lands, particularly in rural areas of the United States, continue to lack access to broadband Internet and cellular connectivity [19]. Inspired by previous observations of community content similarity in tribal networks, we propose FiDO, a community-based Web browsing and content delivery system that takes advantage of user mobility, opportunistic connectivity, and collaborative filtering to provide relevant Web content to members of disconnected households via opportunistic contact with cellular base stations during a daily commute. We evaluate FiDO using trace-driven simulations with network usage data collected from a tribal-operated ISP that serves the Coeur d’Alene Indian Reservation in Western Idaho. By collecting data about household Web preferences and applying a collaborative filtering technique based on the Web usage patterns of the surrounding reservation community, we are able to opportunistically browse the Web on behalf of members of disconnected households, providing an average of 69.4 Web pages (all content from a specific URL, e.g., “http://gis.cdatribe-nsn.gov/LandBuyBack/”) crawled from 73% of their top 10 most visited Web domains (e.g., “cdatribe-nsn.gov” or “cnn.com/”) per day. Moreover, this content is able to be fetched and pushed to users even when the opportunistic data rate is limited to an average of only 0.99 Mbps (σ = 0.24 Mbps) and the daily opportunistic connection time is an average of 45.9 minutes (σ = 2.3 minutes). Additionally, we demonstrate a hybrid “search and browse” approach that allocates a percentage of opportunistic resources to the download of user-specified content. By dedicating only 10% of opportunistic windows of connectivity to the download of social media content, 51% of households were able to receive all of their daily expected social media content in addition to an average of 55.3 Web pages browsed on their behalf from an average of 4 different Web domains. Critically, we demonstrate the feasibility of a collaborative and community-based Web browsing model that extends access to Web content across the last mile(s) using existing infrastructure and rural patterns of mobility.
Actions and Attributes from Wholes and Parts
(2015)

We investigate the importance of parts for the tasks of action and attribute classification. We develop a part-based approach by leveraging convolutional network features inspired by recent advances in computer vision. Our part detectors are a deep version of poselets and capture parts of the human body under a distinct set of poses. For the tasks of action and attribute classification, we train holistic convolutional neural networks and show that adding parts leads to top-performing results for both tasks. We observe that for deeper networks parts are less significant. In addition, we demonstrate the effectiveness of our approach when we replace an oracle person detector, as is the default in the current evaluation protocol for both tasks, with a state-of-the-art person detection system.
Evaluating abdominal core muscle fatigue: Assessment of the validity and reliability of the prone bridging test.
(2018)

The aims of this study were to research the amplitude and median frequency characteristics of selected abdominal, back, and hip muscles of healthy subjects during a prone bridging endurance test, based on surface electromyography (sEMG), (a) to determine if the prone bridging test is a valid field test to measure abdominal muscle fatigue, and (b) to evaluate if the current method of administrating the prone bridging test is reliable. Thirty healthy subjects participated in this experiment. The sEMG activity of seven abdominal, back, and hip muscles was bilaterally measured. Normalized median frequencies were computed from the EMG power spectra. The prone bridging tests were repeated on separate days to evaluate inter and intratester reliability. Significant differences in normalized median frequency slope (NMFslope ) values between several abdominal, back, and hip muscles could be demonstrated. Moderate-to-high correlation coefficients were shown between NMFslope values and endurance time. Multiple backward linear regression revealed that the test endurance time could only be significantly predicted by the NMFslope of the rectus abdominis. Statistical analysis showed excellent reliability (ICC=0.87-0.89). The findings of this study support the validity and reliability of the prone bridging test for evaluating abdominal muscle fatigue.
ProfileDroid: multi-layer profiling of android applications
(2012)

The Android platform lacks tools for assessing and monitoring apps in a systematic way. This lack of tools is particularly problematic when combined with the open nature of Google Play, the main app distribution channel. As our key contribution, we design and implement ProfileDroid, a comprehensive, multi-layer system for monitoring and profiling apps. Our approach is arguably the first to profile apps at four layers: (a) static, or app specification, (b) user interaction, (c) operating system, and (d) network. We evaluate 27 free and paid Android apps and make several observations: (a) we identify discrepancies between the app specification and app execution, (b) free versions of apps could end up costing more than their paid counterparts, due to an order of magnitude increase in traffic, (c) most network traffic is not encrypted, (d) apps communicate with many more sources than users might expect---as many as 13, and (e) we find that 22 out of 27 apps communicate with Google during execution. ProfileDroid is the first step towards a systematic approach for (a) generating cost-effective but comprehensive app profiles, and (b) identifying inconsistencies and surprising behaviors.
Playing Atari Games with Deep Reinforcement Learning and Human Checkpoint Replay
(2016)

This paper introduces a novel method for learning how to play the most difficult Atari 2600 games from the Arcade Learning Environment using deep reinforcement learning. The proposed method, called human checkpoint replay, consists in using checkpoints sampled from human gameplay as starting points for the learning process. This is meant to compensate for the difficulties of current exploration strategies, such as ε-greedy, to find successful control policies in games with sparse rewards. Like other deep reinforcement learning architectures, our model uses a convolutional neural network that receives only raw pixel inputs to estimate the state value function. We tested our method on Montezuma’s Revenge and Private Eye, two of the most challenging games from the Atari platform. The results we obtained show a substantial improvement compared to previous learning approaches, as well as over a random player. We also propose a method for training deep reinforcement learning agents using human gameplay experience, which we call human experience replay.
Approximation by superpositions of a sigmoidal function
(1989)

Abstr,,ct. In this paper we demonstrate that finite linear combinations of compositions of a fixed, univariate function and a set ofaffine functionals can uniformly approximate any continuous function of n real variables with support in the unit hypercube; only mild conditions are imposed on the univariate function. Our results settle an open question about representability in the class of single bidden layer neural networks. In particular, we show that arbitrary decision regions can be arbitrarily well approximated by continuous feedforward neural networks with only a single internal, hidden layer and any continuous sigmoidal nonlinearity. The paper discusses approximation properties of other possible types of nonlinearities that might be implemented by artificial neural networks.
Satellite Image Analysis for Disaster and Crisis-Management Support
(2007)

This paper describes how multisource satellite data and efficient image analysis may successfully be used to conduct rapid-mapping tasks in the domain of disaster and crisis-management support. The German Aerospace Center (DLR) has set up a dedicated crosscutting service, which is the so-called "Center for satellite-based Crisis Information" (ZKI), to facilitate the use of its Earth-observation capacities in the service of national and international response to major disaster situations, humanitarian relief efforts, and civil security issues. This paper describes successful rapid satellite mapping campaigns supporting disaster relief and demonstrates how this technology can be used for civilian crisis-management purposes. During the last years, various international coordination bodies were established, improving the disaster-response-related cooperation within the Earth-observation community worldwide. DLR/ZKI operates in this context, closely networking with public authorities (civil security), nongovernmental organizations (humanitarian relief organizations), satellite operators, and other space agencies. This paper reflects on several of these international activities, such as the International Charter Space and Major Disasters, describes mapping procedures, and reports on rapid-mapping experiences gained during various disaster-response applications. The example cases presented cover rapid impact assessment after the Indian Ocean Tsunami, forest fires mapping for Portugal, earthquake-damage assessment for Pakistan, and landslide extent mapping for the Philippines
Toward a Science of Cyber–Physical System Integration
(2012)

System integration is the elephant in the china store of large-scale cyber-physical system (CPS) design. It would be hard to find any other technology that is more undervalued scientifically and at the same time has bigger impact on the presence and future of engineered systems. The unique challenges in CPS integration emerge from the heterogeneity of components and interactions. This heterogeneity drives the need for modeling and analyzing cross-domain interactions among physical and computational/networking domains and demands deep understanding of the effects of heterogeneous abstraction layers in the design flow. To address the challenges of CPS integration, significant progress needs to be made toward a new science and technology foundation that is model based, precise, and predictable. This paper presents a theory of composition for heterogeneous systems focusing on stability. Specifically, the paper presents a passivity-based design approach that decouples stability from timing uncertainties caused by networking and computation. In addition, the paper describes cross-domain abstractions that provide effective solution for model-based fully automated software synthesis and high-fidelity performance analysis. The design objectives demonstrated using the techniques presented in the paper are group coordination for networked unmanned air vehicles (UAVs) and high-confidence embedded control software design for a quadrotor UAV. Open problems in the area are also discussed, including the extension of the theory of compositional design to guarantee properties beyond stability, such as safety and performance.
An evaluation of alternative architectures for transaction processing in the cloud
(2010)

Cloud computing promises a number of advantages for the deployment of data-intensive applications. One important promise is reduced cost with a pay-as-you-go business model. Another promise is (virtually) unlimited throughput by adding servers if the workload increases. This paper lists alternative architectures to effect cloud computing for database applications and reports on the results of a comprehensive evaluation of existing commercial cloud services that have adopted these architectures. The focus of this work is on transaction processing (i.e., read and update workloads), rather than analytics or OLAP workloads, which have recently gained a great deal of attention. The results are surprising in several ways. Most importantly, it seems that all major vendors have adopted a different architecture for their cloud services. As a result, the cost and performance of the services vary significantly depending on the workload.
Integrated Dual-Channel X-Band Offset-Transmitter for Phase Steering and DDMA Arrays
(2016)

Multiple-Input and Multiple-Output (MIMO) arrays provide more degrees of freedom than conventional phased arrays. They require that every transmitting element of the array can be identified when received. One way to achieve this is to give every element its own unique frequency. Offset-transmitters may be used to introduce MIMO or Doppler Division Multiple Access (DDMA) into phased-arrays without an excessive increase in waveform-generating hardware. Our dual-channel demonstrator IC can obtain a phase accuracy better than 1 degree and an spurious level of better than -65dBc for a single on-chip channel. This work investigates at X-band the effects of the limited on-chip isolation of 35dB, when multiple offset outputs are generated on a single chip for both beam steering and DDMA. In case of beam steering, the requirements on channel-to-channel isolation are less strict, making it well within reach. In the case of DDMA, we recommend increasing the channel-to-channel isolation by implementing multiple chips, in which case independent signals can be generated.
Semi-supervised Semantic Pattern Discovery with Guidance from Unsupervised Pattern Clusters
(2010)

We present a simple algorithm for clustering semantic patterns based on distributional similarity and use cluster memberships to guide semi-supervised pattern discovery. We apply this approach to the task of relation extraction. The evaluation results demonstrate that our novel bootstrapping procedure significantly outperforms a standard bootstrapping. Most importantly, our algorithm can effectively prevent semantic drift and provide semi-supervised learning with a natural stopping criterion.
A Theoretical Basis for a Biopharmaceutic Drug Classification: The Correlation of in Vitro Drug Product Dissolution and in Vivo Bioavailability
(1995)

A biopharmaceutics drug classification scheme for correlating in vitro drug product dissolution and in vivo bioavailability is proposed based on recognizing that drug dissolution and gastrointestinal permeability are the fundamental parameters controlling rate and extent of drug absorption. This analysis uses a transport model and human permeability results for estimating in vivo drug absorption to illustrate the primary importance of solubility and permeability on drug absorption. The fundamental parameters which define oral drug absorption in humans resulting from this analysis are discussed and used as a basis for this classification scheme. These Biopharmaceutic Drug Classes are defined as: Case 1. High solubility-high permeability drugs, Case 2. Low solubility-high permeability drugs, Case 3. High solubility-low permeability drugs, and Case 4. Low solubility-low permeability drugs. Based on this classification scheme, suggestions are made for setting standards for in vitro drug dissolution testing methodology which will correlate with the in vivo process. This methodology must be based on the physiological and physical chemical properties controlling drug absorption. This analysis points out conditions under which no in vitro-in vivo correlation may be expected e.g. rapidly dissolving low permeability drugs. Furthermore, it is suggested for example that for very rapidly dissolving high solubility drugs, e.g. 85% dissolution in less than 15 minutes, a simple one point dissolution test, is all that may be needed to insure bioavailability. For slowly dissolving drugs a dissolution profile is required with multiple time points in systems which would include low pH, physiological pH, and surfactants and the in vitro conditions should mimic the in vivo processes. This classification scheme provides a basis for establishing in vitro-in vivo correlations and for estimating the absorption of drugs based on the fundamental dissolution and permeability properties of physiologic importance.
A Survey of Enabling Technologies of Low Power and Long Range Machine-to-Machine Communications
(2017)

Low power and long range machine-to-machine (M2M) communication techniques are expected to provide ubiquitous connections for the wireless devices. In this paper, three major low power and long range M2M solutions are surveyed. The first type of solutions is referred to as the low power wide area (LPWA) network. The design of the LPWA techniques features low cost, low data rate, long communication range, and low power consumption. The second type of solutions is the IEEE 802.11ah which features higher data rates using a wider bandwidth than the LPWA-based solutions. The third type of solutions is operated under the cellular network infrastructure. Based on the analysis of the pros and cons of the enabling technologies of the surveyed M2M solutions, as well as the corresponding deployment strategies, the gaps in knowledge are identified. The paper also presents a summary of the research directions for improving the performance of the surveyed low power and long range M2M communication technologies.
A New Bit-Serial Architecture for Field Multiplication Using Polynomial Bases
(2008)

Multiplication is the main finite field arithmetic operation in elliptic curve cryptography and its bit-serial hardware implementation is attractive in resource constrained environments such as smart cards, where the chip area is limited. In this paper, a new serial-output bitserial multiplier using polynomial bases over binary extension fields is proposed. It generates a bit of the multiplication in each clock cycle with the latency of one cycle. To the best of our knowledge, this is the first time that such a serial-output bit-serial multiplier architecture using polynomial bases for general irreducible polynomials is proposed.
DBpedia SPARQL Benchmark - Performance Assessment with Real Queries on Real Data
(2011)

Triple stores are the backbone of increasingly many Data Web applications. It is thus evident that the performance of those stores is mission critical for individual projects as well as for data integration on the Data Web in general. Consequently, it is of central importance during the implementation of any of these applications to have a clear picture of the weaknesses and strengths of current triple store implementations. In this paper, we propose a generic SPARQL benchmark creation procedure, which we apply to the DBpedia knowledge base. Previous approaches often compared relational and triple stores and, thus, settled on measuring performance against a relational database which had been converted to RDF by using SQL-like queries. In contrast to those approaches, our benchmark is based on queries that were actually issued by humans and applications against existing RDF data not resembling a relational schema. Our generic procedure for benchmark creation is based on query-log mining, clustering and SPARQL feature analysis. We argue that a pure SPARQL benchmark is more useful to compare existing triple stores and provide results for the popular triple store implementations Virtuoso, Sesame, Jena-TDB, and BigOWLIM. The subsequent comparison of our results with other benchmark results indicates that the performance of triple stores is by far less homogeneous than suggested by previous benchmarks.
Bioinspired engineering of thermal materials.
(2015)

In the development of next-generation materials with enhanced thermal properties, biological systems in nature provide many examples that have exceptional structural designs and unparalleled performance in their thermal or nonthermal functions. Bioinspired engineering thus offers great promise in the synthesis and fabrication of thermal materials that are difficult to engineer through conventional approaches. In this review, recent progress in the emerging area of bioinspired advanced materials for thermal science and technology is summarized. State-of-the-art developments of bioinspired thermal-management materials, including materials for efficient thermal insulation and heat transfer, and bioinspired materials for thermal/infrared detection, are highlighted. The dynamic balance of bioinspiration and practical engineering, the correlation of inspiration approaches with the targeted applications, and the coexistence of molecule-based inspiration and structure-based inspiration are discussed in the overview of the development. The long-term outlook and short-term focus of this critical area of advanced materials engineering are also presented.
Empirical Study on the Healing Nature of Mandalas
(2007)

Mandalas were first used in therapy by Carl Jung, who found that the act of drawing mandalas had a calming effect on patients while at the same time facilitating psychic integration. There is a scarcity of controlled empirical studies of the healing impact of mandalas on mental health. Based on the efficacy of James Pennebaker’s written disclosure paradigm in promoting mental well-being (Pennebaker, 1997a, 1997b), the purpose of our study was to examine the benefits for those suffering from post traumatic stress disorder (PTSD) of processing traumatic events through the creation of mandalas. Benefits to participants were measured in terms of changes in the variables of PTSD symptoms, depressive symptoms, anxiety, spiritual meaning, and the frequency of physical symptoms and illness. Relative to those in the control condition, individuals assigned to the experimental mandala-creation group reported greater decreases in symptoms of trauma at the 1-month follow up. There were no other statistically significant outcome differences. Alternative modes of processing traumatic events (e.g., visually symbolically) may serve individuals who are either reluctant or unable to write about their experiences.
Improving the Performance of the FFT-based Parallel Code-phase Search Acquisition of GNSS Signals by Decomposition of the Circular Correlation
(2012)

Dr. Cyril Botteron leads the GNSS and UWB groups in the electronics and signal processing laboratory at EPFL. He received his PhD degree from the University of Calgary, Canada, in 2003. His current research interests comprise the development of low power radio frequency (RF) integrated circuits and advanced signal processing techniques for ultra-low power communications and global and local positioning applications.
ButterflyNet: a mobile capture and access system for field biology research
(2006)

Through a study of field biology practices, we observed that biology fieldwork generates a wealth of heterogeneous information, requiring substantial labor to coordinate and distill. To manage this data, biologists leverage a diverse set of tools, organizing their effort in paper notebooks. These observations motivated ButterflyNet, a mobile capture and access system that integrates paper notes with digital photographs captured during field research. Through ButterflyNet, the activity of leafing through a notebook expands to browsing all associated digital photos. ButterflyNet also facilitates the transfer of captured content to spreadsheets, enabling biologists to share their work. A first-use study with 14 biologists found this system to offer rich data capture and transformation, in a manner felicitous with current practice.
An extra low-power 1Tbit/s bandwidth PLL/DLL-less eDRAM PHY using 0.3V low-swing IO for 2.5D CoWoS application
(2013)

A 1Tbit/s bandwidth PHY is demonstrated through 2.5D CoWoS platform. Two chips: SOC and eDRAM have been fabricated in TSMC 40nm CMOS technology and stacked on another silicon interposer chip in 65nm technology. Total 1024 DQ bus operating in 1.1Gbit/s with Vmin=0.3V are proven in experimental results. A novel timing compensation mechanism is presented to achieve a low-power and small area eDRAM PHY that excludes PLL/DLL but retains good timing margin. Another data sampling alignment training approach is reserved to enhance timing robustness. A compact low-swing IO also achieves great power efficiency of 0.105mW/Gbps.